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Credit Exposure and Expected Loss update Suresh Pabbisetty, FRM, ERP, CQF, CSQA. Lead Technical Analyst, Credit February 17, 2016.

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Presentation on theme: "Credit Exposure and Expected Loss update Suresh Pabbisetty, FRM, ERP, CQF, CSQA. Lead Technical Analyst, Credit February 17, 2016."— Presentation transcript:

1 Credit Exposure and Expected Loss update Suresh Pabbisetty, FRM, ERP, CQF, CSQA. Lead Technical Analyst, Credit February 17, 2016

2 Agenda Background Inputs and assumptions Exposure and collateral distributions Expected loss estimates Observations

3 PUBLIC Credit Exposure and Expected Loss update Background 3

4 PUBLIC Credit Exposure and Expected Loss update Background: –As part of the discussion on ERCOT market risk appetite, staff presented an analysis of market exposure to CWG/MCWG in November 2015 –CWG/MCWG was requested to provide a quarterly update of the analysis 4

5 PUBLIC Credit Exposure and Expected Loss update Inputs and Assumptions 5

6 PUBLIC Credit Exposure and Expected Loss update Inputs and Assumptions: –Only Active Counter-Parties are included –Counter-Parties are classified by rating and market activity –TPE and collateral balances used are averages for January 2016 –Negative excess collateral shown is due to the adjustment to remove unsecured credit –Counter-Parties that are subsidiaries of, or guaranteed by, rated entities are given the parent/guarantor’s rating, adjusted down one notch –Recovery Rate (RR) is assumed 0 6

7 PUBLIC Credit Exposure and Expected Loss update Inputs and Assumptions: –Exposure at Default (EaD) is assumed to be equal to TPE TPE will typically exceed invoice exposure, so this is a conservative metric. It should be viewed as a relative indicator of credit portfolio risk, not a forecast for losses or uplift –Probabilities of Default (PD) from “Global Corporate Average Cumulative Default Rates By Rating Modifier (1981-2014)”, from S&P publication “2014 Annual Global Corporate Default Study And Rating Transitions” –Expected Loss (EL) computed as follows; EL = EaD * PD * (1-RR) 7

8 PUBLIC Credit Exposure and Expected Loss update Inputs and Assumptions: –Assumed 1 year Probabilities of Default 8

9 PUBLIC Credit Exposure and Expected Loss update Exposure and Collateral Distributions 9

10 PUBLIC Credit Exposure and Expected Loss update Summary statistics by market segment 10

11 PUBLIC Credit Exposure and Expected Loss update Summary statistics by Counter-Party / parent / guarantor rating 11

12 PUBLIC Credit Exposure and Expected Loss update Active Counter-Parties distribution by rating and activity type 12

13 PUBLIC Credit Exposure & Expected Loss update January 2016 Total Potential Exposure distribution 13

14 PUBLIC Credit Exposure & Expected Loss update January 2016 Average Excess Collateral distribution 14

15 PUBLIC Credit Exposure & Expected Loss update January 2016 based Expected Loss Exposure distribution 15

16 PUBLIC Credit Exposure and Expected Loss update Observations 16

17 PUBLIC Credit Exposure and Expected Loss update Observations: –Traders constitute the largest share of Counter-Parties, but Load + Gen accounts for a majority (~63.5%) of TPE –Load-only Counter-Parties account for only about 4% of exposure –Two-thirds of Counter-Parties are unrated, but these account for only one-third of TPE. –Most exposure is in the Load + Gen segment, with the second largest component among traders. –Because of the high concentration of low- or un-rated Counter- Parties, Loss Given Default is 22% of TPE. 17

18 PUBLIC Credit Exposure and Expected Loss update Questions 18


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